Department of Statistics (Biostatistics), School of Medicine, University of Granada, Avenida de la Investigación 11, 18016, Granada, Spain.
BMC Med Res Methodol. 2020 Jun 5;20(1):143. doi: 10.1186/s12874-020-00988-y.
The comparison of the performance of two binary diagnostic tests is an important topic in Clinical Medicine. The most frequent type of sample design to compare two binary diagnostic tests is the paired design. This design consists of applying the two binary diagnostic tests to all of the individuals in a random sample, where the disease status of each individual is known through the application of a gold standard. This article presents an R program to compare parameters of two binary tests subject to a paired design.
The "compbdt" program estimates the sensitivity and the specificity, the likelihood ratios and the predictive values of each diagnostic test applying the confidence intervals with the best asymptotic performance. The program compares the sensitivities and specificities of the two diagnostic tests simultaneously, as well as the likelihood ratios and the predictive values, applying the global hypothesis tests with the best performance in terms of type I error and power. When the global hypothesis test is significant, the causes of the significance are investigated solving the individual hypothesis tests and applying the multiple comparison method of Holm. The most optimal confidence intervals are also calculated for the difference or ratio between the respective parameters. Based on the data observed in the sample, the program also estimates the probability of making a type II error if the null hypothesis is not rejected, or estimates the power if the if the alternative hypothesis is accepted. The "compbdt" program provides all the necessary results so that the researcher can easily interpret them. The estimation of the probability of making a type II error allows the researcher to decide about the reliability of the null hypothesis when this hypothesis is not rejected. The "compbdt" program has been applied to a real example on the diagnosis of coronary artery disease.
The "compbdt" program is one which is easy to use and allows the researcher to compare the most important parameters of two binary tests subject to a paired design. The "compbdt" program is available as supplementary material.
比较两种二分类诊断试验的性能是临床医学中的一个重要课题。比较两种二分类诊断试验最常见的样本设计类型是配对设计。这种设计包括将两种二分类诊断试验应用于随机样本中的所有个体,其中每个个体的疾病状态通过应用金标准来确定。本文介绍了一种用于比较配对设计下两种二分类试验参数的 R 程序。
“compbdt”程序应用具有最佳渐近性能的置信区间来估计每种诊断试验的敏感性和特异性、似然比和预测值。该程序同时比较两种诊断试验的敏感性和特异性,以及似然比和预测值,应用具有最佳 I 型错误和功效的全局假设检验。当全局假设检验显著时,通过解决个体假设检验并应用 Holm 的多重比较方法来调查显著的原因。还为各自参数之间的差异或比值计算了最优化的置信区间。基于样本中观察到的数据,该程序还估计了如果不拒绝零假设,则犯 II 类错误的概率,或者如果接受备择假设,则估计功效。“compbdt”程序提供了所有必要的结果,以便研究人员可以轻松解释它们。犯 II 类错误的概率的估计允许研究人员在不拒绝零假设时决定该假设的可靠性。“compbdt”程序已应用于冠状动脉疾病诊断的真实示例。
“compbdt”程序易于使用,允许研究人员比较配对设计下两种二分类试验的最重要参数。“compbdt”程序可作为补充材料获得。